In the field of parallel imaging (PI), alongside image-domain regulariza...
In this paper, a dynamic dual-graph fusion convolutional network is prop...
Model evolution and constant availability of data are two common phenome...
Magnetic resonance imaging (MRI) is known to have reduced signal-to-nois...
Click-through rate (CTR) prediction is of great importance in recommenda...
Recently, untrained neural networks (UNNs) have shown satisfactory
perfo...
Click-Through Rate (CTR) prediction plays a key role in online advertisi...
Click-through rate (CTR) Prediction is of great importance in real-world...
Click-through rate (CTR) prediction is a crucial task in web search,
rec...
Learning to capture feature relations effectively and efficiently is
ess...
In autonomous driving, navigation through unsignaled intersections with ...
Pedestrian trajectory prediction is a critical yet challenging task,
esp...
Accurate pedestrian trajectory prediction is of great importance for
dow...
Forecasting human trajectories is critical for tasks such as robot crowd...
Safe and efficient crowd navigation for mobile robot is a crucial yet
ch...
Vision-based autonomous driving through imitation learning mimics the
be...
Imitation learning by behavioral cloning is a prevalent method which has...
End-to-end visual-based imitation learning has been widely applied in
au...